基于支持向量机的轨道结构病害识别研究

轨道结构作为承载列车载荷的关键部件,一旦出现病害将直接影响列车的行驶安全.针对这一问题,文中提出了一种基于支持向量机的轨道结构病害识别方法.该方法利用时域统计和离散小波变换对轨道结构不同工况,例如正常状态、轨枕空吊、道床板结下轨枕振动加速度数据进行联合特征提取,降低了数据的维度,为病害识别提供了可能.该方法还利用支持向...

Research on Track Structure Damage Identification Based on Support Vector Machine

The track structure is a key component that carries the load of the train. Once a disease occurs, it will directly affect the safety of the train. To solve this problem, a method for identifying the track structure disease based on a support vector machine is proposed. This method uses time-domain statistics and discrete wavelet transform to perform joint feature extraction on the vibration acceleration data of the sleeper under different working conditions of the track structure, such as normal state, unsupported sleeper and cement hardening, which reduces the dimensionality of data and provides the possibility for disease identification. The method also uses the support vector machine algorithm to identify the feature vector, and uses the grid search method to select the parameters of the support vector machine, so that the recognition accuracy rate reaches about 85%. The experimental results show that the proposed method can better identify different degrees of unsupported sleeper and cement hardening, and provide a technical basis for online early warning of track structure failure.